Qwen for Customer Support Training in Thimphu, Bhutan

The Qwen for Customer Support Training is a practical, role-focused program designed to help organizations use Qwen large language models to modernize customer support operations.
The course covers how to build AI-powered chatbots, ticket triage systems, agent-assist tools, and knowledge-driven support workflows that improve response speed, consistency, and customer satisfaction.

This training is ideal for customer support teams, CX leaders, operations managers, product teams, and solution architects.

Introduction to AI in Customer Support

• Evolution of customer support with AI

• Where Qwen fits in the support lifecycle

• Self-service vs agent-assisted AI

• Common support automation use cases

Customer Support Data & Knowledge Sources

• FAQs, manuals, policies, and SOPs

• Ticket history and chat transcripts

• Structured vs unstructured support data

• Preparing data for AI-driven support

Prompt Engineering for Customer Support

• Designing prompts for accurate responses

• Tone control and brand voice

• Handling ambiguous and incomplete queries

• Reducing hallucinations in customer replies

AI Chatbots & Virtual Assistants

• Designing support chat flows

• Single-turn vs multi-turn conversations

• Handling FAQs and repetitive questions

• Escalation to human agents

Ticket Classification & Automation

• Categorizing and tagging support tickets

• Priority and sentiment detection

• Automated routing and assignment

• SLA-aware response generation

Knowledge-Based Support (Grounded AI)

• Answering from internal knowledge bases

• Context injection and grounding techniques

• Keeping responses up to date

• Managing conflicting or outdated information

Agent Assist & Productivity Tools

• Suggested replies and summaries

• Call and chat summarization

• Next-best-action recommendations

• Reducing agent handling time

Multilingual & Global Support

• Language detection and translation

• Consistent responses across regions

• Cultural and tone considerations

• Scaling global customer support

Quality, Accuracy & Customer Experience

• Measuring response quality

• Confidence vs uncertainty handling

• Customer satisfaction considerations

• Continuous improvement loops

Security, Privacy & Compliance

• Handling sensitive customer data

• Access control and data masking

• Compliance and audit requirements

• Responsible AI in customer support

Deployment & Scaling Strategy

• Rolling out AI support solutions

• Monitoring performance and usage

• Scaling support automation safely

• Managing updates and improvements

Hands-on Exercises

Summary and Conclusion